RT Journal Article
ID 6d565a286507f124
A1 Sakata, Sei-ichiro
A1 Ashida, F.
A1 Shimizu, Y.
T1 INVERSE STOCHASTIC HOMOGENIZATION ANALYSIS FOR A PARTICLE-REINFORCED COMPOSITE MATERIAL WITH THE MONTE CARLO SIMULATION
JF International Journal for Multiscale Computational Engineering
JO JMC
YR 2011
FD 2011-06-30
VO 9
IS 4
SP 409
OP 423
K1 inverse stochastic homogenization
K1 stochastic homogenization
K1 homogenization problem,optimization
K1 composite material
AB This paper proposes a numerical method for identifying microscopic randomness in an elastic property of a component material of a particle-reinforced composite material. Some reports on the stochastic homogenization analysis considering a microscopic random variation can be found in the literature. A microscopic stress field is influenced by the microscopic variation, and stochastic microscopic stress analysis is also important. In the previous reports it is assumed that the microscopic random variation is known. However, it is sometimes difficult to identify a microscopic random variation in a composite material, especially after the manufacturing process. Therefore, an identification process for microscopic randomness by solving an inverse problem is needed for the stochastic microscopic stress analysis. This kind of problem is called "inverse stochastic homogenization." In this paper solving an inverse stochastic homogenization problem is attempted with inverse homogenization analysis and Monte Carlo simulation is used for the stochastic homogenization analysis. The inverse homogenization analysis is performed with the homogenization method and an optimization technique. Some techniques for the inverse stochastic homogenization analysis with the Monte Carlo simulation are developed. With numerical results, validity and accuracy of the methods are discussed.
PB Begell House
LK http://dl.begellhouse.com/journals/61fd1b191cf7e96f,2c2262e958d8b1f7,6d565a286507f124.html